{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7702392f-0a04-4cf8-90f8-8c2d2c42454e",
   "metadata": {},
   "source": [
    "Chapter 22\n",
    "# 最小生成树\n",
    "Book_6《数据有道》 | 鸢尾花书：从加减乘除到机器学习"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "680ec991-b1a0-4d5a-b1bd-7fed25e5a3a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "358ff927-cb5c-44dc-9bc2-1e37fbf011b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构造图\n",
    "G = nx.Graph()\n",
    "\n",
    "# 创建边\n",
    "G.add_edges_from([(0, 1, {\"weight\": 4}),\n",
    "                  (0, 7, {\"weight\": 8}),\n",
    "                  (1, 7, {\"weight\": 11}),\n",
    "                  (1, 2, {\"weight\": 8}),\n",
    "                  (2, 8, {\"weight\": 2}),\n",
    "                  (2, 5, {\"weight\": 4}),\n",
    "                  (2, 3, {\"weight\": 7}),\n",
    "                  (3, 4, {\"weight\": 9}),\n",
    "                  (3, 5, {\"weight\": 14}),\n",
    "                  (4, 5, {\"weight\": 10}),\n",
    "                  (5, 6, {\"weight\": 2}),\n",
    "                  (6, 8, {\"weight\": 6}),\n",
    "                  (7, 8, {\"weight\": 7})])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "01a88642-e6a4-4519-861b-60d180928417",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the graph and the minimum spanning tree\n",
    "pos = nx.spring_layout(G)\n",
    "\n",
    "# 可视化\n",
    "nx.draw_networkx_nodes(G, \n",
    "                       pos, \n",
    "                       node_color=\"0.8\", \n",
    "                       node_size=500)\n",
    "\n",
    "edge_labels = nx.get_edge_attributes(G, \n",
    "                                     \"weight\")\n",
    "\n",
    "nx.draw_networkx_edges(G, \n",
    "                       pos, \n",
    "                       edge_color=edge_labels.values(),\n",
    "                       edge_cmap=plt.cm.RdYlBu_r,\n",
    "                       width = 3)\n",
    "\n",
    "nx.draw_networkx_labels(G, \n",
    "                        pos, \n",
    "                        font_size=12, \n",
    "                        font_family=\"sans-serif\")\n",
    "\n",
    "edge_labels = {(u, v): d[\"weight\"] for u, v, d in G.edges(data=True)}\n",
    "nx.draw_networkx_edge_labels(G, \n",
    "                             pos, \n",
    "                             edge_labels=edge_labels)\n",
    "\n",
    "plt.axis(\"off\")\n",
    "plt.savefig('图.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8fa36d71-57cd-4453-8a81-f08c337c5105",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 找到最小生成树\n",
    "T = nx.minimum_spanning_tree(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c3edf930-2a38-4917-8fda-fae7388b3a37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the graph and the minimum spanning tree\n",
    "pos = nx.spring_layout(G)\n",
    "\n",
    "# 可视化\n",
    "nx.draw_networkx_nodes(G, \n",
    "                       pos, \n",
    "                       node_color=\"0.8\", \n",
    "                       node_size=500)\n",
    "\n",
    "edge_labels = nx.get_edge_attributes(G, \n",
    "                                     \"weight\")\n",
    "\n",
    "nx.draw_networkx_edges(G, \n",
    "                       pos, \n",
    "                       edge_color=edge_labels.values(),\n",
    "                       edge_cmap=plt.cm.RdYlBu_r,\n",
    "                       width = 3)\n",
    "\n",
    "nx.draw_networkx_labels(G, \n",
    "                        pos, \n",
    "                        font_size=12, \n",
    "                        font_family=\"sans-serif\")\n",
    "\n",
    "edge_labels = {(u, v): d[\"weight\"] for u, v, d in G.edges(data=True)}\n",
    "nx.draw_networkx_edge_labels(G, \n",
    "                             pos, \n",
    "                             edge_labels=edge_labels)\n",
    "\n",
    "nx.draw_networkx_edges(T, \n",
    "                       pos, \n",
    "                       style = '--',\n",
    "                       edge_color=\"black\", \n",
    "                       width=1)\n",
    "plt.axis(\"off\")\n",
    "plt.savefig('最小生成树.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f2a0646-e50c-4838-b791-f23f3741a210",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4bba6e00-9267-43af-ad80-0bacdc616696",
   "metadata": {},
   "source": [
    "参考： \n",
    "https://networkx.org/documentation/stable/auto_examples/graph/plot_mst.html"
   ]
  },
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   "execution_count": null,
   "id": "bc0f47bb-2f2a-4beb-b193-aeacf501e136",
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   "outputs": [],
   "source": []
  }
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